Dubious Arctic ice data does not support the official storyline

Figure 1 is demonstrating the impossibility of the commonly provided assertions by the scientific community of an exponential or similar melt away of Arctic ice. A very precise (13 term) annual cycle has been hindcast from daily data back into detrended monthly data. The model was rebased to monthly and subtracted from actual monthly data.

Any curvature must appear in one or both of the straight line trend or residual. It does not.

Figure 1 also exhibits the satellite usage timeline. Each one of these satellites occupied a different orbit, all but one definitely a decaying orbit leading to Nyquist issues which are liable to alias to a long term trend. The instruments carried were all different and used different processing software. All instruments had a different observation field geometry. Human judgement has been used to attempt filling in where sensing surface polorisation destroys contrast, sea surface and ice looking the same. Modelling is used where there is unknown data. And other issues.

Residual change in recent years (refer figure 1)

A problem peculiar to the Arctic but not Antarctica is what I will deem the limit effect.

The consequence is ice is free to melt by varying amounts but it is not free to extend except in limited sea lanes. An asymmetric regime is present.

In recent years there has been an increase in the amplitude of the annual ice cycle where it is easy to only consider only half the effect, reducing. Increase is muted by hitting land. A novel idea here is produce a composite dataset which includes information from land data. Simple way would be bring in the Rutgers snow data.

It is possible the effect is as much about data error. Why this has changed is not discussed here.

How feasible is the linear trend?

Simply, nature does not do straight lines. I’ve looked hard and cannot find a rational degree of curvature, which would need to be very slow.

I conclude the linear trend is a human artefact originating in the joining of dataset fragments. This suggests the data is not particularly good.

Off the top of my head I don’t know which is g02135 and which is IJIS/JAXA (plotted a few weeks ago, details of how this was done not stated)

Given the published data is not actually raw, is filtered [not by me], there are slight differences but does not seem to be material.

The whole data at daily

Figure 4

This demonstrates the questionable nature of the data because the annual cycle must be consistent but is not although from this figure you can’t see the whole story. A fingerprint.

Although not easily visible there is a slight 5 to 6 year undulation in the data which probably means 2013 will show a slight ice increase, 2012 being a low point of this cycle as was 2007 (7 8 9 10 11 12, 5 years)